Expanding the scope of a catalogue search to bioisosteric fragment merges using a graph database approach
Stephanie WillsiD, Rubén Sánchez-GarcíaiD, Stephen D. RoughleyiD, Andy T. MerrittiD, Roderick E. HubbardiD, F. von DelftiD, Charlotte Mary DeaneiD
Abstract
The efficiency of fragment-to-lead optimization could be improved by automated workflows for the design of follow-up compounds. Pipelines that are able to fully exploit the interaction opportunities identified from the crystal structures of bound fragments would greatly aid this goal. To do so, these pipelines need to require minimal intervention from the user and be computationally efficient. In this work, we describe an updated version of our fragment merging methodology, which provides several feature enhancements, primarily by expanding the chemical space searched, allowing the identification of more diverse follow-up compounds, thus maximizing the chances of finding successful hits. While the original method focused on finding perfect merges, meaning compounds that directly incorporate substructures from the original fragments, here we expand the search to what we term bioisosteric merges, involving the incorporation of substructures that replicate the pharmacophoric features of the original fragments but may not be exactly identical. Unlike existing pharmacophore and shape-based descriptors used for virtual screening, this approach combines the search for these properties with the incorporation of novelty, which is necessary when searching for ways to link together distinct substructures. Compared with perfect merging, our new approach is able to find compounds that are directly informed by structures within the original fragments but are more chemically diverse. We contrast our approach with the use of a pharmacophore-constrained docking pipeline, run in parallel for select fragment pairs, and show that our method requires between 1.1-45.9-fold less computational time for conformer generation per merging hit identified, referring to compounds that show a favourable degree of shape and colour overlap and recapitulation of original fragment interactions. Overall, our results show that our method has potential to be used to generate designs inspired by all fragments within a given pocket.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 4
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- The use of a graph database is a complementary approach to a classical similarity search for identifying commercially available fragment merges
Stephanie Wills, Rubén Sánchez-García, … Charlotte Mary Deane·Journal of Chemical Information and ModelingPeer-reviewed·May 25, 2023
- Efficient Hit-to-Lead Searching of Kinase Inhibitor Chemical Space via Computational Fragment Merging
G. V. Andrianov, W. J. G. Ong, … J. Karanicolas·bioRxiv·Jun 1, 2021
- INTERPOLATION-BASED CONDITIONING OF FLOW MATCHING MODELS FOR BIOISOSTERIC LIGAND DESIGN
Yael Ziv, Martin Buttenschoen, … Charlotte Mary Deane·bioRxiv·Oct 20, 2025
- MOZAIC: Compound Growth via In Silico Reactions and Global Optimization using Conformational Space Annealing
JinHyeok Yoo, Woong‐Hee Shin·BioinformaticsPeer-reviewed·Aug 1, 2026
- FragmentScope - exploring the fragment space with learned surface representations
Evgenia Elizarova, Irina Morozova, … Bruno E. Correia·bioRxiv·Dec 18, 2025
- KinaFrag explores the kinase-ligand fragment interaction space for selective kinase inhibitor discovery
Zhi-Zheng Wang, Xing-Xing Shi, … Guang‐Fu Yang·bioRxiv·Mar 28, 2021